Applying a Reference Objects Preselection Algorithm to Real-World Data


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Abstract

The problem of optimal selection of learning objects is investigated. The effectiveness of the previously proposed iterative method for generating sets of relevant precedents is demonstrated on real-world data.

About the authors

N. N. Bondarenko

Faculty of Computational Mathematics and Cybernetics

Author for correspondence.
Email: kolianmos1@gmail.com
Russian Federation, Moscow

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